Matching Items (4)
Filtering by
- All Subjects: Adjustment (Psychology)
- All Subjects: factor analysis
- Creators: Aiken, Leona S.
Description
Recent reports have indicated that there are both mental health and educational disparities between Latino youth and their European American counterparts. Specifically, Latin youth are at a heightened risk for negative mental health outcomes in comparison to their non-Latino youth (e.g., Eaton et al., 2008). Further, 16.7% of Latino adolescents dropped out of high school compared to 5.3% of European American youth over the past several decades (1960-2011; U.S. Department of Education, 2013). Mexican American (M.A. youth in particular, have the lowest educational attainment among all Latino ethnic groups in the U.S. (U.S. Census Bureau, 2010). While these mental health and educational disparities have often been attributed to discrimination experiences that Latino youth encounter, there is also consistent empirical evidence linking discrimination with these maladjustment problems. These studies confirmed that discrimination directly related to depressive symptoms (e.g., Umana-Taylor et al., 2007), externalizing behaviors (Berkel et al., 2010), self-esteem (e.g., Zeiders et al., 2013), and academic outcomes (e.g., Umana-Taylor et al., 2012). Few studies to date have examined the underlying mechanisms (i.e., moderation and mediation) that help us to better understand resiliency paths for those Latino youth that display positive adjustment outcomes despite being faced with similar discrimination encounters that their maladjusted peers face. Therefore, the following two studies examined various mechanisms in which discrimination related to adjustment to better understand potential risk and resiliency processes in hopes of informing intervention research. Paper 1 explored cultural influences on the association between discrimination, active coping, and mental health outcomes in M.A. youth. Paper 2 examined how trajectories of discrimination across 5th, 7th, and 10th grades related to cultural values, externalizing behaviors, and academic outcomes in M.A. youth. Taken together, these studies provide a culturally informed overview of adjustment processes in M.A. adolescents who face discrimination in addition to identifying critical directions for future research in efforts to gaining a more contextualized and comprehensive understanding of the dynamic processes involved in discrimination and adjustment in M.A. youth.
ContributorsO'Donnell, Megan (Author) / Roosa, Mark W. (Thesis advisor) / Dumka, Larry (Committee member) / Gonzales, Nancy (Committee member) / Barrera, Manuel (Committee member) / Arizona State University (Publisher)
Created2014
Description
Although the issue of factorial invariance has received increasing attention in the literature, the focus is typically on differences in factor structure across groups that are directly observed, such as those denoted by sex or ethnicity. While establishing factorial invariance across observed groups is a requisite step in making meaningful cross-group comparisons, failure to attend to possible sources of latent class heterogeneity in the form of class-based differences in factor structure has the potential to compromise conclusions with respect to observed groups and may result in misguided attempts at instrument development and theory refinement. The present studies examined the sensitivity of two widely used confirmatory factor analytic model fit indices, the chi-square test of model fit and RMSEA, to latent class differences in factor structure. Two primary questions were addressed. The first of these concerned the impact of latent class differences in factor loadings with respect to model fit in a single sample reflecting a mixture of classes. The second question concerned the impact of latent class differences in configural structure on tests of factorial invariance across observed groups. The results suggest that both indices are highly insensitive to class-based differences in factor loadings. Across sample size conditions, models with medium (0.2) sized loading differences were rejected by the chi-square test of model fit at rates just slightly higher than the nominal .05 rate of rejection that would be expected under a true null hypothesis. While rates of rejection increased somewhat when the magnitude of loading difference increased, even the largest sample size with equal class representation and the most extreme violations of loading invariance only had rejection rates of approximately 60%. RMSEA was also insensitive to class-based differences in factor loadings, with mean values across conditions suggesting a degree of fit that would generally be regarded as exceptionally good in practice. In contrast, both indices were sensitive to class-based differences in configural structure in the context of a multiple group analysis in which each observed group was a mixture of classes. However, preliminary evidence suggests that this sensitivity may contingent on the form of the cross-group model misspecification.
ContributorsBlackwell, Kimberly Carol (Author) / Millsap, Roger E (Thesis advisor) / Aiken, Leona S. (Committee member) / Enders, Craig K. (Committee member) / Mackinnon, David P (Committee member) / Arizona State University (Publisher)
Created2011
Description
Female infertility can present a significant challenge to quality of life. To date, few, if any investigations have explored the process by which women adapt to premature ovarian insufficiency (POI), a specific type of infertility, over time. The current investigation proposed a bi-dimensional, multi-factor, model of adjustment characterized by the identification of six latent factors representing personal attributes (resilience resources and vulnerability), coping (adaptive and maladaptive) and outcomes (distress and wellbeing). Measures were collected over the period of one year; personal attributes were assessed at Time 1, coping at Time 2 and outcomes at Time 3. It was hypothesized that coping factors would mediate associations between personal attributes and outcomes. Confirmatory Factor Analysis (CFA), simple regressions and single mediator models were utilized to test study hypotheses. Overall, with the exception of coping, the factor structure was consistent with predictions. Two empirically derived coping factors, and a single standalone strategy, avoidance, emerged. The first factor, labeled "approach coping" was comprised of strategies directly addressing the experience of infertility. The second was comprised of strategies indicative of "letting go /moving on." Only avoidance significantly mediated the association between vulnerability and distress.
ContributorsDriscoll, Mary (Author) / Davis, Mary C. (Thesis advisor) / Aiken, Leona S. (Committee member) / Luecken, Linda J. (Committee member) / Zautra, Alex J. (Committee member) / Arizona State University (Publisher)
Created2011
Description
In the past, it has been assumed that measurement and predictive invariance are consistent so that if one form of invariance holds the other form should also hold. However, some studies have proven that both forms of invariance only hold under certain conditions such as factorial invariance and invariance in the common factor variances. The present research examined Type I errors and the statistical power of a method that detects violations to the factorial invariant model in the presence of group differences in regression intercepts, under different sample sizes and different number of predictors (one or two). Data were simulated under two models: in model A only differences in the factor means were allowed, while model B violated invariance. A factorial invariant model was fitted to the data. Type I errors were defined as the proportion of samples in which the hypothesis of invariance was incorrectly rejected, and statistical power was defined as the proportion of samples in which the hypothesis of factorial invariance was correctly rejected. In the case of one predictor, the results show that the chi-square statistic has low power to detect violations to the model. Unexpected and systematic results were obtained regarding the negative unique variance in the predictor. It is proposed that negative unique variance in the predictor can be used as indication of measurement bias instead of the chi-square fit statistic with sample sizes of 500 or more. The results of the two predictor case show larger power. In both cases Type I errors were as expected. The implications of the results and some suggestions for increasing the power of the method are provided.
ContributorsAguilar, Margarita Olivera (Author) / Millsap, Roger E. (Thesis advisor) / Aiken, Leona S. (Committee member) / Enders, Craig K. (Committee member) / Arizona State University (Publisher)
Created2010